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ISDS 2018 Conference Abstracts

Updating syndromic surveillnce baselines following 
public health interventions
Roger Morbey, Alex Elliot, Andre Charlett, Sally Harcourt* and Gillian Smith
Public Health England, Birmingham, United Kingdom

Objective
To adjust modelled baselines used for syndromic surveillance to 

account for public health interventions. Specifically to account for 
a change in the seasonality of diarrhoea and vomiting indicators 
following the introduction of a rotavirus vaccine in England.

Introduction
Public Health England’s syndromic surveillance service monitor 

presentations for gastrointestinal illness to detect increases in health 
care seeking behaviour driven by infectious gastrointestinal disease. 
We use regression models to create baselines for expected activity and 
then identify any periods of signficant increases. The introduction of a 
rotavirus vaccine in England during July 2013 (Bawa, Z. et al. 2015) 
led to a reduction in incidence of the disease, requiring a readjustment 
of baselines.

Methods
We identified syndromes where rates had dropped significantly 

following the vaccine’s introduction. For these indicators, we 
introduced new variables into the regression models used to create 
baselines. Specifically we tested for a ‘step-change’ drop in rates and 
a change in the seasonality of baselines. Finally we checked the new 
models accuracy against actual syndromic data before and after the 
vaccine introduction.

Results
We were able to improve model fit post-intervention, with the 

best-fitting models based on a change in seasonality. All post-
intervention regression models had reduced average residual square 
error. Reductions in residual errors ranged from <1% to 60% when a 
‘step-change’ variable was included and 4% to 75% when accounting 
for seasonality. Furthermore, every syndrome showed a better model 
fit when a change in seasonality was included.

Conclusions
Prior to the vaccine’s introduction, rotavirus caused a spring-time 

peak in vomiting and diarrhoea recorded by syndromic surveillance 
systems. Failure to account for the reduction in this peak post-vaccine 
would have made surveillance systems less effective. In particular, 
any increased activity during spring may have been undetected. 
Moreover, models that did not account for changes in seasonality 
would increase the chances of false alarms during other seasons. 
By adjusting our baselines for the changes in seasonality due to the 
vaccine we were able to maintain effective surveillance systems.

Selected syndromic indicators with baselines before and after intervention.

Keywords
intervention; aberration detection; syndromic; rotavirus

Acknowledgments
RM, AE, and GS are supported by the National Institute of Health 
Research’s (NIHR) Health Protection Research Unit in Emergency 
Preparedness and Response. The views expressed are those of the 
author(s) and not necessarily those of the NHS, the NIHR, the Department 
of Health or Public Health England.

References
Bawa, Z., et al. Assessing the Likely Impact of a Rotavirus Vaccination 

Program in England: The Contribution of Syndromic Surveillance. 
Clinical infectious diseases : an official publication of the Infectious 
Diseases Society of America 2015;61(1):77-85.

*Sally Harcourt
E-mail: sally.harcourt@phe.gov.uk

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 10(1):e25, 2018